Computational modeling analysis for cell growth using Electric Cell-substrate Impedance Sensing (ECIS) based time series data

In this paper, a computational modeling analysis on cell growth is presented. This study aims at deriving a mathematical model for cell growth in order to understand, analyze and predict the complex mechanisms of cell biological systems. The proposed model was derived and validated using the practically measured cell growth curves produced by an existing novel on-line monitoring technique, referred to as Electric Cell-substrate Impedance Sensing (ECIS). The model in the form of a time response function may reflect the resistance change as a result of cell proliferation. Model parameters were then estimated by fitting the measured time series impedance data to the model itself. Preliminary analysis results indicated that the computational model proposed in this study possessed good potentials to modeling analysis on cell growth and thus could provide a hopeful start for subsequent quantitative investigations into cell dynamics.